A Dna Algorithm for the Batimetric Mapping in the Lagoon of Venice Using Quickbird Multispectral Data

During the last decade, several studies have focused on the use of passive multispectral remote sensing to derive the bathymetry in coastal zone. In particular, data acquired with the SPOT and the Landsat TM/ETM+ sensors have been used to derive models of bathymetry at medium scales. Until now, the successful application of passive remote sensing techniques to bathymetry mapping was restricted to costal zones with clear water and small changes in the seabed, but with the availability of the high resolution satellites (IKONOS, Eros-A1, QuickBird, SPOT-5), researchers have a new powerful tools to study environmental phenomenon at large scale. This paper focus on the use of high resolution imagery to estimate water depths in a lagoon environment. Starting from the depth of penetration zone method proposed by Jupp for costal bathymetry mapping, a new genetic algorithm was developed for lagoon bathymetry mapping. The potential use of the QuickBird multispectral data, together with the new algorithm developed, was tested in a complex environment such as the lagoon of Venice (Italy). Several tests have been performed into five different test sites (S.Erasmo littoral, Treporti canal, S. Felice canal, Canesa canal and Bari canal), where 18 radiometric transects were traced to study the lagoon bathymetry. The accuracy of the batimetric measures was assessed by using other known soundings depth points within the test area. An interesting correlation between the real and the computed bathymetry was found. The limit of a such analysis lies in the correct calibration of the model, that, for the complex lagoon ecosystem, is not a simple task. * Corresponding author.